This notebook parses the eprime files into BIDS valid events TSVs.
if (!require("pacman")) install.packages("pacman")
## Loading required package: pacman
pacman::p_load(rprime, dplyr, tidyverse, rjson)
Let’s start with an example:
rp <- read_eprime("~/dropbox/rawbx/RTG1_1ITCscanner1LLA-05200-1.txt")
experiment_data <- FrameList(rp)
message("Structure of eprime:")
## Structure of eprime:
print(preview_frames(experiment_data))
##
## Eprime.Level Running Procedure
## 1 Header Header
## List of 17
## $ Eprime.Level : num 1
## $ Eprime.LevelName : chr "Header_"
## $ Eprime.Basename : chr "RTG1_1ITCscanner1LLA-05200-1"
## $ Eprime.FrameNumber : chr "1"
## $ Procedure : chr "Header"
## $ Running : chr "Header"
## $ VersionPersist : chr "1"
## $ LevelName : chr "LogLevel10"
## $ Experiment : chr "RTG1_1ITCscanner1LLA"
## $ SessionDate : chr "06-10-2011"
## $ SessionTime : chr "13:30:30"
## $ SessionTimeUtc : chr "5:30:30 PM"
## $ Subject : chr "05200"
## $ Session : chr "1"
## $ RandomSeed : chr "1055496015"
## $ Group : chr "1"
## $ Display.RefreshRate: chr "60.052"
## - attr(*, "class")= chr [1:2] "EprimeFrame" "list"
##
## Eprime.Level Running Procedure
## 3 TrialList TrialProc
## List of 66
## $ Eprime.Level : num 3
## $ Eprime.LevelName : chr "TrialList_1"
## $ Eprime.Basename : chr "RTG1_1ITCscanner1LLA-05200-1"
## $ Eprime.FrameNumber : chr "2"
## $ Procedure : chr "TrialProc"
## $ Running : chr "TrialList"
## $ Offer : chr "23"
## $ delay : chr "21"
## $ NullDuration : chr "5000"
## $ LeftRight : chr "0"
## $ FeedbackDur : chr "1672"
## $ Cycle : chr "1"
## $ Sample : chr "1"
## $ nullscreen.OnsetDelay : chr "303"
## $ nullscreen.OnsetTime : chr "54348"
## $ nullscreen.DurationError : chr "-303"
## $ nullscreen.StartTime : chr "54047"
## $ nullscreen.OffsetTime : chr "58845"
## $ nullscreen.FinishTime : chr "58845"
## $ nullscreen.ActionDelay : chr "0"
## $ nullscreen.ActionTime : chr "54348"
## $ nullscreen.OffsetDelay : chr "0"
## $ Choice1.OnsetDelay : chr "0"
## $ Choice1.OnsetTime : chr "59045"
## $ Choice1.DurationError : chr "-999999"
## $ Choice1.Duration : chr "4000"
## $ Choice1.StartTime : chr "58846"
## $ Choice1.OffsetTime : chr "61373"
## $ Choice1.FinishTime : chr "61373"
## $ Choice1.OffsetDelay : chr "-999999"
## $ Choice1.RTTime : chr "61373"
## $ Choice1.RT : chr "2328"
## $ Choice1.RESP : chr "y"
## $ Choice1.CRESP : chr "r"
## $ FeedbackDisplay6.OnsetDelay : chr "939"
## $ FeedbackDisplay6.OnsetTime : chr "62312"
## $ FeedbackDisplay6.DurationError : chr "-939"
## $ FeedbackDisplay6.Duration : chr "1672"
## $ FeedbackDisplay6.StartTime : chr "62310"
## $ FeedbackDisplay6.OffsetTime : chr "62845"
## $ FeedbackDisplay6.FinishTime : chr "62845"
## $ FeedbackDisplay6.OffsetDelay : chr "0"
## $ Choice.OnsetDelay : chr "0"
## $ Choice.OnsetTime : chr "0"
## $ Choice.DurationError : chr "0"
## $ Choice.Duration : chr "4000"
## $ Choice.StartTime : chr "0"
## $ Choice.OffsetTime : chr "0"
## $ Choice.FinishTime : chr "0"
## $ Choice.TargetOffsetTime : chr "0"
## $ Choice.TargetOnsetTime : chr "0"
## $ Choice.OffsetDelay : chr "0"
## $ Choice.RTTime : chr "0"
## $ Choice.RT : chr "0"
## $ Choice.RESP : chr ""
## $ Choice.CRESP : chr ""
## $ FeedbackDisplay3.OnsetDelay : chr "0"
## $ FeedbackDisplay3.OnsetTime : chr "0"
## $ FeedbackDisplay3.DurationError : chr "0"
## $ FeedbackDisplay3.Duration : chr "0"
## $ FeedbackDisplay3.StartTime : chr "0"
## $ FeedbackDisplay3.OffsetTime : chr "0"
## $ FeedbackDisplay3.FinishTime : chr "0"
## $ FeedbackDisplay3.TargetOffsetTime: chr "0"
## $ FeedbackDisplay3.TargetOnsetTime : chr "0"
## $ FeedbackDisplay3.OffsetDelay : chr "0"
## - attr(*, "class")= chr [1:2] "EprimeFrame" "list"
##
## Eprime.Level Running Procedure
## 2 BlockList BlockProc
## List of 9
## $ Eprime.Level : num 2
## $ Eprime.LevelName : chr "BlockList_1"
## $ Eprime.Basename : chr "RTG1_1ITCscanner1LLA-05200-1"
## $ Eprime.FrameNumber: chr "52"
## $ Procedure : chr "BlockProc"
## $ Running : chr "BlockList"
## $ PracticeMode : chr "?"
## $ Cycle : chr "1"
## $ Sample : chr "1"
## - attr(*, "class")= chr [1:2] "EprimeFrame" "list"
##
## Eprime.Level Running Procedure
## 1 <NA> <NA>
## List of 65
## $ Eprime.Level : num 1
## $ Eprime.LevelName : logi NA
## $ Eprime.Basename : chr "RTG1_1ITCscanner1LLA-05200-1"
## $ Eprime.FrameNumber : chr "53"
## $ Procedure : logi NA
## $ Running : logi NA
## $ Experiment : chr "RTG1_1ITCscanner1LLA"
## $ SessionDate : chr "06-10-2011"
## $ SessionTime : chr "13:30:30"
## $ SessionTimeUtc : chr "5:30:30 PM"
## $ Subject : chr "05200"
## $ Session : chr "1"
## $ RandomSeed : chr "1055496015"
## $ Group : chr "1"
## $ Display.RefreshRate : chr "60.052"
## $ Slide2.OnsetDelay : chr "19"
## $ Slide2.OnsetTime : chr "8774"
## $ Slide2.DurationError : chr "-999999"
## $ Slide2.PreRelease : chr "0"
## $ Slide2.Duration : chr "-1"
## $ Slide2.StartTime : chr "8755"
## $ Slide2.OffsetTime : chr "19995"
## $ Slide2.FinishTime : chr "19995"
## $ Slide2.TimingMode : chr "0"
## $ Slide2.CustomOnsetTime : chr "0"
## $ Slide2.CustomOffsetTime : chr "0"
## $ Slide2.ActionDelay : chr "0"
## $ Slide2.ActionTime : chr "8774"
## $ Slide2.TargetOffsetTime : chr "-1"
## $ Slide2.TargetOnsetTime : chr "8755"
## $ Slide2.OffsetDelay : chr "-999999"
## $ Slide2.RTTime : chr "19995"
## $ Slide2.ACC : chr "0"
## $ Slide2.RT : chr "11221"
## $ Slide2.RESP : chr "n"
## $ Slide2.CRESP : chr ""
## $ Slide1.OnsetTime : chr "20000"
## $ Slide1.DurationError : chr "-999999"
## $ Slide1.Duration : chr "-1"
## $ Slide1.StartTime : chr "19998"
## $ Slide1.OffsetTime : chr "54045"
## $ Slide1.FinishTime : chr "54045"
## $ Slide1.RT : chr "34045"
## $ Goodbye.OnsetDelay : chr "2"
## $ Goodbye.OnsetTime : chr "558047"
## $ Goodbye.DurationError : chr "0"
## $ Goodbye.PreRelease : chr "0"
## $ Goodbye.Duration : chr "6000"
## $ Goodbye.StartTime : chr "557853"
## $ Goodbye.OffsetTime : chr "564047"
## $ Goodbye.FinishTime : chr "564047"
## $ Goodbye.TimingMode : chr "0"
## $ Goodbye.CustomOnsetTime : chr "0"
## $ Goodbye.CustomOffsetTime: chr "0"
## $ Goodbye.ActionDelay : chr "1"
## $ Goodbye.ActionTime : chr "558048"
## $ Goodbye.TargetOffsetTime: chr "564047"
## $ Goodbye.TargetOnsetTime : chr "558045"
## $ Goodbye.OffsetDelay : chr "0"
## $ Goodbye.RTTime : chr "0"
## $ Goodbye.ACC : chr "0"
## $ Goodbye.RT : chr "0"
## $ Goodbye.RESP : chr ""
## $ Goodbye.CRESP : chr ""
## $ Clock.StartTimeOfDay : chr "6/10/2011 1:30:30 PM"
## - attr(*, "class")= chr [1:2] "EprimeFrame" "list"
## NULL
trial <- filter_in(experiment_data, "Running", "TrialList")
block <- filter_in(experiment_data, "Running", "BlockList")
slides <- filter_in(experiment_data, "Eprime.Level", 1)
slides_df <- to_data_frame(slides) %>%
readr::type_convert()
##
## ── Column specification ────────────────────────────────────────────────────────
## cols(
## .default = col_double(),
## Eprime.LevelName = col_character(),
## Eprime.Basename = col_character(),
## Procedure = col_character(),
## Running = col_character(),
## LevelName = col_character(),
## Experiment = col_character(),
## SessionDate = col_character(),
## SessionTime = col_time(format = ""),
## SessionTimeUtc = col_time(format = ""),
## Subject = col_character(),
## Slide2.RESP = col_character(),
## Slide2.CRESP = col_logical(),
## Goodbye.RESP = col_logical(),
## Goodbye.CRESP = col_logical(),
## Clock.StartTimeOfDay = col_character()
## )
## ℹ Use `spec()` for the full column specifications.
trial_df <- to_data_frame(trial) %>%
readr::type_convert()
##
## ── Column specification ────────────────────────────────────────────────────────
## cols(
## .default = col_double(),
## Eprime.LevelName = col_character(),
## Eprime.Basename = col_character(),
## Procedure = col_character(),
## Running = col_character(),
## Choice1.RESP = col_character(),
## Choice1.CRESP = col_character(),
## Choice.RESP = col_character(),
## Choice.CRESP = col_character()
## )
## ℹ Use `spec()` for the full column specifications.
head(trial_df)
## Eprime.Level Eprime.LevelName Eprime.Basename Eprime.FrameNumber
## 1 3 TrialList_1 RTG1_1ITCscanner1LLA-05200-1 2
## 2 3 TrialList_2 RTG1_1ITCscanner1LLA-05200-1 3
## 3 3 TrialList_3 RTG1_1ITCscanner1LLA-05200-1 4
## 4 3 TrialList_4 RTG1_1ITCscanner1LLA-05200-1 5
## 5 3 TrialList_5 RTG1_1ITCscanner1LLA-05200-1 6
## 6 3 TrialList_6 RTG1_1ITCscanner1LLA-05200-1 7
## Procedure Running Offer delay NullDuration LeftRight FeedbackDur Cycle
## 1 TrialProc TrialList 23.0 21 5000 0 1672 1
## 2 TrialProc TrialList 28.0 5 5000 1 2328 1
## 3 TrialProc TrialList 30.5 55 5000 1 1984 1
## 4 TrialProc TrialList 39.0 34 17000 1 2440 1
## 5 TrialProc TrialList 25.0 7 8000 0 1736 1
## 6 TrialProc TrialList 22.5 45 2000 1 2584 1
## Sample nullscreen.OnsetDelay nullscreen.OnsetTime nullscreen.DurationError
## 1 1 303 54348 -303
## 2 2 0 63045 0
## 3 3 0 72045 0
## 4 4 0 81045 0
## 5 5 0 102045 0
## 6 6 0 114045 0
## nullscreen.StartTime nullscreen.OffsetTime nullscreen.FinishTime
## 1 54047 58845 58845
## 2 62853 67845 67845
## 3 71854 76845 76845
## 4 80853 97845 97845
## 5 101854 109845 109845
## 6 113853 115845 115845
## nullscreen.ActionDelay nullscreen.ActionTime nullscreen.OffsetDelay
## 1 0 54348 0
## 2 0 63045 0
## 3 0 72045 0
## 4 0 81045 0
## 5 0 102045 0
## 6 0 114045 0
## Choice1.OnsetDelay Choice1.OnsetTime Choice1.DurationError Choice1.Duration
## 1 0 59045 -999999 4000
## 2 0 59045 -999999 4000
## 3 0 59045 -999999 4000
## 4 0 59045 -999999 4000
## 5 0 110045 -999999 4000
## 6 0 110045 -999999 4000
## Choice1.StartTime Choice1.OffsetTime Choice1.FinishTime Choice1.OffsetDelay
## 1 58846 61373 61373 -999999
## 2 58846 61373 61373 -999999
## 3 58846 61373 61373 -999999
## 4 58846 61373 61373 -999999
## 5 109846 112309 112309 -999999
## 6 109846 112309 112309 -999999
## Choice1.RTTime Choice1.RT Choice1.RESP Choice1.CRESP
## 1 61373 2328 y r
## 2 61373 2328 y r
## 3 61373 2328 y r
## 4 61373 2328 y r
## 5 112309 2264 y r
## 6 112309 2264 y r
## FeedbackDisplay6.OnsetDelay FeedbackDisplay6.OnsetTime
## 1 939 62312
## 2 939 62312
## 3 939 62312
## 4 939 62312
## 5 3 112312
## 6 3 112312
## FeedbackDisplay6.DurationError FeedbackDisplay6.Duration
## 1 -939 1672
## 2 -939 1672
## 3 -939 1672
## 4 -939 1672
## 5 -3 1736
## 6 -3 1736
## FeedbackDisplay6.StartTime FeedbackDisplay6.OffsetTime
## 1 62310 62845
## 2 62310 62845
## 3 62310 62845
## 4 62310 62845
## 5 112311 113845
## 6 112311 113845
## FeedbackDisplay6.FinishTime FeedbackDisplay6.OffsetDelay Choice.OnsetDelay
## 1 62845 0 0
## 2 62845 0 0
## 3 62845 0 0
## 4 62845 0 0
## 5 113845 0 0
## 6 113845 0 0
## Choice.OnsetTime Choice.DurationError Choice.Duration Choice.StartTime
## 1 0 0 4000 0
## 2 68045 -999999 4000 67846
## 3 77045 -999999 4000 76846
## 4 98045 -999999 4000 97847
## 5 98045 -999999 4000 97847
## 6 116045 -999999 4000 115846
## Choice.OffsetTime Choice.FinishTime Choice.TargetOffsetTime
## 1 0 0 0
## 2 69717 69717 71845
## 3 79061 79061 80845
## 4 99605 99605 101845
## 5 99605 99605 101845
## 6 117461 117461 119845
## Choice.TargetOnsetTime Choice.OffsetDelay Choice.RTTime Choice.RT Choice.RESP
## 1 0 0 0 0 <NA>
## 2 68045 -999999 69717 1672 y
## 3 77045 -999999 79061 2016 r
## 4 98045 -999999 99605 1560 r
## 5 98045 -999999 99605 1560 r
## 6 116045 -999999 117461 1416 r
## Choice.CRESP FeedbackDisplay3.OnsetDelay FeedbackDisplay3.OnsetTime
## 1 <NA> 0 0
## 2 r 3 69720
## 3 r 3 79064
## 4 r 3 99608
## 5 r 3 99608
## 6 r 3 117464
## FeedbackDisplay3.DurationError FeedbackDisplay3.Duration
## 1 0 0
## 2 -3 2328
## 3 -3 1984
## 4 -3 2440
## 5 -3 2440
## 6 -3 2584
## FeedbackDisplay3.StartTime FeedbackDisplay3.OffsetTime
## 1 0 0
## 2 69719 71845
## 3 79063 80845
## 4 99607 101845
## 5 99607 101845
## 6 117463 119845
## FeedbackDisplay3.FinishTime FeedbackDisplay3.TargetOffsetTime
## 1 0 0
## 2 71845 71845
## 3 80845 80845
## 4 101845 101845
## 5 101845 101845
## 6 119845 119845
## FeedbackDisplay3.TargetOnsetTime FeedbackDisplay3.OffsetDelay
## 1 0 0
## 2 69717 0
## 3 79061 0
## 4 99605 0
## 5 99605 0
## 6 117461 0
Each line of this table indicates an event (trial) happening in the experiment. In an ITC task, participants are shown a value of money and a delay. They’re asked, “would you rather receive $20 now, or wait X number of days to receive $Y later?” Hence, each line is an offer in this paradigm.
Processing
We want to get this into BIDS standard. Here’s the proposed columns:
Mandatory in BIDS:
onset: time that the trial happened from the start of the scan
duration: how long that event happened for
Required for ITC
choice: did they choose the delayed offer or not
button_press: did they go left or right
amount: how much they were offered
delay: what was the delay on the offer
reaction time: how long did they take to make their decision
Data Wrangling
The first thing we need to define is what choice they made. The column LeftRight indicates whether the instant $20 option is on the left or right of the screen. If LeftRight == 1, the delayed option was presented on the left.
We’ll code this as a factor delay_position with two levels, 1 to indicate it was on the right, and 0 to indicate it was on the left:
trial_df_proc <- trial_df %>%
select(-contains("null"), -contains("Eprime"), -contains("Feedback")) %>%
mutate(delay_position = ifelse(LeftRight == 0, 1, 0))
Next, we define which button they pressed, left (0) or right (1):
We’ll also define the motor response they made, button_press, as either 1 (right) or 0 (left). We use CHOICE.RESP and CHOICE1.RESP as the indicator of which side they picked. If the delayed option was on the left, use CHOICE.RESP; r is right, y is left.
Then, we encode the choice as either 1=delayed (the delayed position and the chosen button press where the same) or 0=now (the delayed position and the chosen button press where different):
trial_df_proc <- trial_df_proc %>%
mutate(
button_press = case_when(
LeftRight == 1 & Choice.RESP == "y" ~ 0,
LeftRight == 1 & Choice.RESP == "r" ~ 1,
LeftRight == 0 & Choice1.RESP == "y" ~ 0,
LeftRight == 0 & Choice1.RESP == "r" ~ 1
),
choice = case_when(
LeftRight == 1 & Choice.RESP == "y" ~ 1,
LeftRight == 1 & Choice.RESP == "r" ~ 0,
LeftRight == 0 & Choice1.RESP == "y" ~ 0,
LeftRight == 0 & Choice1.RESP == "r" ~ 1
)
)
We also include the amount and delay:
trial_df_proc <- trial_df_proc %>%
rename(offer = Offer) %>%
select(offer, delay, choice, button_press, delay_position, everything())
The duration of the trial is uniform at 4000ms. There are two columns for event timings: Choice1.OnsetTime and Choice.OnsetTime. If LeftRight==1 the task proceeds to Choice.*. If they clicked right, the time for this gets recorded in Choice.OnsetTime, and the value in Choice1.OnsetTime is duplicated from the previous row:
10 216687 222699 ## left
11 228727 222699 ## left
12 246744 222699 ## right
13 246744 264762 ## right
14 246744 270774 ## right
Here we use the duplicated function to tell us if a value in a vector is a duplicate of itself. If there’s a duplicate, take the value from the opposite column:
trial_df_proc <- trial_df_proc %>%
mutate(
onset = case_when(
# the first row should both not be duplicates
!duplicated(Choice.OnsetTime) & !duplicated(Choice1.OnsetTime) ~ 0,
# if any value in Choice is a duplicate, choose the value from Choice1
duplicated(Choice.OnsetTime) ~ Choice1.OnsetTime,
# vice versa
duplicated(Choice1.OnsetTime) ~ Choice.OnsetTime
),
duration = 4000,
) %>%
select(onset, duration, everything())
We can do the same for response time:
trial_df_proc <- trial_df_proc %>%
mutate(
row_num = row_number(),
response_time = case_when(
# the first row should be the one that's not zero
row_num == 1 & Choice.RT == 0 ~ Choice1.RT,
row_num == 1 & Choice1.RT == 0 ~ Choice.RT,
# if any value in Choice is a duplicate, choose the value from Choice1
duplicated(Choice.RT) ~ Choice1.RT,
# vice versa
duplicated(Choice1.RT) ~ Choice.RT
)
) %>%
select(onset, duration, response_time, everything(), -row_num)
Lastly, we have to account for the timepoint that the task began (as opposed to when the participant is reading instructions). This is given in the slides_df:
trial_df_proc <- trial_df_proc %>%
mutate(onset = ifelse(onset == 0, onset, onset - slides_df$Slide1.OffsetTime[2]))
Here’s the data head so far:
trial_df_sv <- trial_df_proc %>%
select(onset:delay_position) %>%
mutate(IA = 20)
trial_df_sv %>%
head()
## onset duration response_time offer delay choice button_press delay_position
## 1 0 4000 2328 23.0 21 0 0 1
## 2 14000 4000 1672 28.0 5 1 0 0
## 3 23000 4000 2016 30.5 55 0 1 0
## 4 44000 4000 1560 39.0 34 0 1 0
## 5 56000 4000 2264 25.0 7 0 0 1
## 6 62000 4000 1416 22.5 45 0 1 0
## IA
## 1 20
## 2 20
## 3 20
## 4 20
## 5 20
## 6 20
From here, we write this data frame to a file.
trial_df_sv %>%
write_delim("/cbica/projects/wolf_satterthwaite_reward/Curation/code/itc_eprime/matlab_code/data/demo_trial.txt", delim = "\t")
Subjective Value
We calculate the k parameter for ITC using a pre-compiled matlab script:
function []=kable_itc_wrapper(inputfile, outputfile)
m = readtable(inputfile);
type='h';
choice = m.('choice');
IA = m.('IA');
DA = m.('offer');
D = m.('delay');
out = KableLab_ITC(type,choice,IA,DA,D);
k_param=out.k;
Tout = table(k_param);
writetable(Tout,outputfile);
disp(k_param);
end
% ------------------------------------- %
% kable lab ITC code starts here
% ------------------------------------- %
function out = KableLab_ITC(type,choice,IA,DA,D)
% data quality control by checking missed trials.
if sum(choice ~= 0 & choice ~= 1) ~= 0
error('choice input has non binary elements')
end
if sum(choice) == length(choice) || sum(choice) == 0
error('choices are all one-sided')
end
% type specifies the type of discounting function
if strcmp(type,'e') || strcmp(type,'h')
out = fitoneparam(type,choice,IA,DA,D);
%elseif strcmp(type,'g')
% out = fitgen(choice,IA,DA,D);
%elseif strcmp(type,'q')
% out = fitquasi(choice,IA,DA,D);
else
error('unknown discounting function type')
end
out.type = type;
[~,dev] = mnrfit([],2-choice); % an intercept-only model
out.LL0 = -dev/2; % LL of a null model
out.r2 = 1 - out.LL/out.LL0; % McFadden's R-squared
out.DV = out.SVlater-IA; % Decision Variable
predictedChoice = out.DV>=0;
out.percentPredicted = sum(predictedChoice == choice) / length(choice) * 100;
out.choicep = 1 ./ (1 + exp(-(out.noise.*out.DV)));
out.choiceresid = out.choicep-choice;
out.rawresid = out.DV-round(max(abs(out.DV))).*(2.*choice-1);
end
function out = fitoneparam(type,choice,IA,DA,D)
if strcmp(type,'e') % exponential case
indiffk = -log(IA./DA)./D;
else % hyperbolic case
indiffk = (DA-IA)./(IA.*D);
end
mink = min(indiffk)*(0.99);
maxk = max(indiffk)*(1.01);
[noise,ks] = meshgrid([-1,0,1], linspace(log(mink),log(maxk),5)); % search grid. We search in logspace
b = [noise(:) ks(:)];
info.negLL = inf;
for i = 1:length(b)
[new.b,new.negLL] = fmincon(@negLL,b(i,:),[],[],[],[],[log(eps),log(mink)],[2,log(maxk)],[],...
optimset('Algorithm','interior-point','Display','off'),choice,IA,DA,D,type);
if new.negLL < info.negLL
info = new;
end
end
out.k = exp(info.b(2));
out.noise = exp(info.b(1));
out.LL = -info.negLL;
if strcmp(type,'e')
out.SVlater = DA.*exp(-out.k.*D);
else
out.SVlater = DA./(1+out.k.*D);
end
end
function negLL = negLL(beta,choice,IA,DA,D,type) % function for negative Log-Likelihood
switch type
case 'e'
SVdelayed = DA.*exp(-exp(beta(2)).*D);
case 'h'
SVdelayed = DA./(1+exp(beta(2)).*D);
case 'q'
SVdelayed = exp(log(DA)+log(beta(2))+D.*log(beta(3)));
beta(1) = log(beta(1));
case 'g'
SVdelayed = DA./((1+exp(beta(2)).*D).^beta(3));
beta(1) = log(beta(1));
end
reg = exp(beta(1)).*(SVdelayed-IA);
p = 1 ./ (1 + exp(-reg));
p(p == 1) = 1-eps;
p(p == 0) = eps;
negLL = -sum((choice==1).*log(p) + (choice==0).*log(1-p));
end
Here’s how it’s called:
./run_kable_itc_wrapper.sh $MATLAB_DIR data/demo_trial.txt data/output_trial.txt
And read it in:
k_param <- read_table("/cbica/projects/wolf_satterthwaite_reward/Curation/code/itc_eprime/matlab_code/data/output_trial.txt") %>%
pull(k_param)
##
## ── Column specification ────────────────────────────────────────────────────────
## cols(
## k_param = col_double()
## )
k_param
## [1] 0.07106205
Finally, subjective value is calculated by \(\frac{\text{offer}} {1 + k \times \text{delay}}\)
final_df <- trial_df_sv %>%
mutate(subjective_value = offer / (1 + k_param * delay)) %>%
mutate_if(~ is.numeric(.) && all(unique(.) %in% c(0, 1, NA)), factor) %>%
select(-IA)
Final Outputs
Here’s the final dataframe:
final_df
## onset duration response_time offer delay choice button_press delay_position
## 1 0 4000 2328 23.0 21 0 0 1
## 2 14000 4000 1672 28.0 5 1 0 0
## 3 23000 4000 2016 30.5 55 0 1 0
## 4 44000 4000 1560 39.0 34 0 1 0
## 5 56000 4000 2264 25.0 7 0 0 1
## 6 62000 4000 1416 22.5 45 0 1 0
## 7 68000 4000 1344 37.5 149 0 1 0
## 8 83000 4000 1200 40.5 97 0 1 0
## 9 95000 4000 1656 31.5 68 0 0 1
## 10 101000 4000 1168 46.5 48 0 1 0
## 11 107000 4000 1544 31.5 48 0 0 1
## 12 125000 4000 1536 27.5 53 0 0 1
## 13 143000 4000 1224 43.0 161 0 1 0
## 14 149000 4000 1536 48.0 107 0 1 0
## 15 161000 4000 3464 41.5 15 1 1 1
## 16 170000 4000 1248 39.0 48 0 0 1
## 17 185000 4000 1048 25.5 149 0 1 0
## 18 191000 4000 1344 20.5 84 0 0 1
## 19 197000 4000 1352 38.0 178 0 0 1
## 20 203000 4000 3168 31.5 7 0 0 1
## 21 209000 4000 1072 25.5 84 0 1 0
## 22 215000 4000 1312 34.0 7 1 1 1
## 23 221000 4000 1272 20.5 161 0 0 1
## 24 233000 4000 1696 41.5 7 1 0 0
## 25 254000 4000 928 28.0 48 0 1 0
## 26 263000 4000 1216 29.0 4 1 1 1
## 27 269000 4000 1128 33.0 55 0 1 0
## 28 278000 4000 1048 47.5 43 0 0 1
## 29 290000 4000 1112 33.0 107 0 0 1
## 30 296000 4000 824 22.5 178 0 1 0
## 31 302000 4000 1016 50.0 124 0 1 0
## 32 308000 4000 1192 30.0 34 0 0 1
## 33 317000 4000 1424 26.5 7 0 1 0
## 34 341000 4000 1032 25.5 124 0 1 0
## 35 347000 4000 880 39.0 124 0 1 0
## 36 356000 4000 1136 25.5 107 0 0 1
## 37 365000 4000 1456 36.5 32 0 1 0
## 38 371000 4000 1128 41.5 178 0 0 1
## 39 380000 4000 760 45.0 149 0 1 0
## 40 386000 4000 1096 44.0 124 0 0 1
## 41 395000 4000 1336 29.0 68 0 0 1
## 42 410000 4000 1488 29.0 17 0 0 1
## 43 419000 4000 2328 26.5 29 0 0 1
## 44 431000 4000 1256 48.0 23 0 0 1
## 45 449000 4000 1368 30.5 97 0 0 1
## 46 455000 4000 1272 44.0 34 0 1 0
## 47 470000 4000 912 47.5 84 0 1 0
## 48 482000 4000 1328 48.0 34 0 1 0
## 49 491000 4000 1136 22.5 124 0 0 1
## 50 500000 4000 1136 28.0 124 0 1 0
## subjective_value
## 1 9.228413
## 2 20.659477
## 3 6.213822
## 4 11.416496
## 5 16.695223
## 6 5.359961
## 7 3.236038
## 8 5.131117
## 9 5.401032
## 10 10.541879
## 11 7.141273
## 12 5.769689
## 13 3.456317
## 14 5.579035
## 15 20.087799
## 16 8.841576
## 17 2.200506
## 18 2.941509
## 19 2.784078
## 20 21.035981
## 21 3.658950
## 22 22.705503
## 23 1.647779
## 24 27.714070
## 25 6.347798
## 26 22.581305
## 27 6.723151
## 28 11.712004
## 29 3.835586
## 30 1.648467
## 31 5.095960
## 32 8.781920
## 33 17.696936
## 34 2.598940
## 35 3.974849
## 36 2.963862
## 37 11.148492
## 38 3.040506
## 39 3.883246
## 40 4.484445
## 41 4.972378
## 42 13.133732
## 43 8.657869
## 44 18.220280
## 45 3.864174
## 46 12.880149
## 47 6.815692
## 48 14.051072
## 49 2.293182
## 50 2.853738
We pair this with a dictionary in BIDS describing how to interpret these columns, like:
{
"column": {
"LongName": "some name",
"Description": "long description",
"Levels": {
"go": "level one of a factor",
"stop": "leve two of a factor",
}
}
}
dictionary <- final_df %>%
select(-onset, -duration) %>%
map(~ list(
LongName = "",
Description = ""
))
dictionary$response_time$LongName <- "Response Time to Offer"
dictionary$response_time$Description <- "How long it takes for the participant to choose and respond with a button press"
dictionary$offer$LongName <- "Offer Amount"
dictionary$offer$Description <- "Amount of money in dollars that the trial is offering"
dictionary$delay$LongName <- "Delay on Offer"
dictionary$delay$Description <- "Number of days to wait until they can receive the offer"
dictionary$choice$LongName <- "Choice made by the participant"
dictionary$choice$Description <- "Factor indicating whether the participant selected an offer of 20 dollars immediately, or an offer of more value at the delayed time"
dictionary$choice$Levels <- list(`1` = "Selected the delayed offer",
`0` = "Selected the immediate offer")
dictionary$button_press$LongName <- "Which button was pressed"
dictionary$button_press$Description <- "Factor indicating whether the participant pressed the button on the right or the left"
dictionary$button_press$Levels <- list(`1` = "Pressed the right hand button",
`0` = "Pressed the left hand button")
dictionary$delay_position$LongName <- "Position of the delayed option"
dictionary$delay_position$Description <- "Factor indicating which side of the screen the delayed option is on for the trial"
dictionary$delay_position$Levels <- list(`1` = "Delay on the right",
`0` = "Delay on the left")
dictionary$subjective_value$LongName <- "Subjective value of potential offer"
dictionary$subjective_value$Description <- "Participant's subjective value of the delayed offer calculated using a discount curve (as is common in the literature)" # should add paper link in here
jsonlite::toJSON(dictionary) %>%
jsonlite::prettify()
## {
## "response_time": {
## "LongName": [
## "Response Time to Offer"
## ],
## "Description": [
## "How long it takes for the participant to choose and respond with a button press"
## ]
## },
## "offer": {
## "LongName": [
## "Offer Amount"
## ],
## "Description": [
## "Amount of money in dollars that the trial is offering"
## ]
## },
## "delay": {
## "LongName": [
## "Delay on Offer"
## ],
## "Description": [
## "Number of days to wait until they can receive the offer"
## ]
## },
## "choice": {
## "LongName": [
## "Choice made by the participant"
## ],
## "Description": [
## "Factor indicating whether the participant selected an offer of 20 dollars immediately, or an offer of more value at the delayed time"
## ],
## "Levels": {
## "1": [
## "Selected the delayed offer"
## ],
## "0": [
## "Selected the immediate offer"
## ]
## }
## },
## "button_press": {
## "LongName": [
## "Which button was pressed"
## ],
## "Description": [
## "Factor indicating whether the participant pressed the button on the right or the left"
## ],
## "Levels": {
## "1": [
## "Pressed the right hand button"
## ],
## "0": [
## "Pressed the left hand button"
## ]
## }
## },
## "delay_position": {
## "LongName": [
## "Position of the delayed option"
## ],
## "Description": [
## "Factor indicating which side of the screen the delayed option is on for the trial"
## ],
## "Levels": {
## "1": [
## "Delay on the right"
## ],
## "0": [
## "Delay on the left"
## ]
## }
## },
## "subjective_value": {
## "LongName": [
## "Subjective value of potential offer"
## ],
## "Description": [
## "Participant's subjective value of the delayed offer calculated using a discount curve (as is common in the literature)"
## ]
## }
## }
##